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Authors: Giovanni Acampora 1 ; Autilia Vitiello 2 ; Ciro Di Nunzio 3 ; Maurizio Saliva 4 and Luciano Garofano 5

Affiliations: 1 Nottingham Trent University, United Kingdom ; 2 University of Salerno, Italy ; 3 University ”Magna Graecia” of Catanzaro, Italy ; 4 Azienda Sanitaria Locale ASL Napoli 3 Sud, Italy ; 5 Arma dei Carabinieri and Italian Academy of Forensic Sciences, Italy

Keyword(s): Forensic Intelligence, Pattern Recognition, Image Processing, Fuzzy Reasoning

Related Ontology Subjects/Areas/Topics: Artificial Intelligence ; Biomedical Engineering ; Biomedical Signal Processing ; Computational Intelligence ; Computer-Supported Education ; Domain Applications and Case Studies ; Fuzzy Systems ; Health Engineering and Technology Applications ; Human-Computer Interaction ; Industrial, Financial and Medical Applications ; Methodologies and Methods ; Neural Networks ; Neurocomputing ; Neurotechnology, Electronics and Informatics ; Pattern Recognition ; Pattern Recognition: Fuzzy Clustering and Classifiers ; Physiological Computing Systems ; Sensor Networks ; Signal Processing ; Soft Computing ; Theory and Methods

Abstract: Bloodstain pattern analysis (BPA) is a forensic discipline that plays a key role in tracing events which caused a bloodshed at a crime scene. Indeed, BPA supports worldwide investigation agencies (US FBI, Italian Carabinieri and so on) in interpreting the morphology and distribution of bloodspots at a crime scene in order to enable a potentially complete reconstruction of the dynamics of the act of violence with a consequent identification of potential suspects for that crime. However, in spite of its importance, this forensic discipline is still based on completely manual approaches, making the analysis of a crime scene long, tedious and potentially imperfect. This position paper is aimed at proving that computational intelligence methodologies can be efficiently integrated with image processing techniques to support forensic investigators in increasing their performance in examining bloodstains, both in terms of time and accuracy of analysis. A preliminary study involving the application of fuzzy clustering has been carried out in order to validate our opinion and stimulate computational intelligence community to face this new challenge towards a formal definition of Forensic Intelligence. (More)

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Paper citation in several formats:
Acampora, G.; Vitiello, A.; Di Nunzio, C.; Saliva, M. and Garofano, L. (2014). Bloodstain Pattern Analysis - A New Challenge for Computational Intelligence Community. In Proceedings of the International Conference on Fuzzy Computation Theory and Applications (IJCCI 2014) - FCTA; ISBN 978-989-758-053-6, SciTePress, pages 211-216. DOI: 10.5220/0005155602110216

@conference{fcta14,
author={Giovanni Acampora. and Autilia Vitiello. and Ciro {Di Nunzio}. and Maurizio Saliva. and Luciano Garofano.},
title={Bloodstain Pattern Analysis - A New Challenge for Computational Intelligence Community},
booktitle={Proceedings of the International Conference on Fuzzy Computation Theory and Applications (IJCCI 2014) - FCTA},
year={2014},
pages={211-216},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0005155602110216},
isbn={978-989-758-053-6},
}

TY - CONF

JO - Proceedings of the International Conference on Fuzzy Computation Theory and Applications (IJCCI 2014) - FCTA
TI - Bloodstain Pattern Analysis - A New Challenge for Computational Intelligence Community
SN - 978-989-758-053-6
AU - Acampora, G.
AU - Vitiello, A.
AU - Di Nunzio, C.
AU - Saliva, M.
AU - Garofano, L.
PY - 2014
SP - 211
EP - 216
DO - 10.5220/0005155602110216
PB - SciTePress